Remote autonomous inspection of utility system components utilizing drones and rovers

ABSTRACT

Unmanned monitoring devices, such as unmanned aerial vehicles (UAV), drones or rovers may inspect system components within an area of interest (AOI) such an electric power distribution system including generation, transmission, and distribution elements for autonomous detection of damage to the components. Work orders for repairing the damage are autonomously generated and resources identified within the work orders are autonomously provisioned.

FIELD OF THE DISCLOSURE

The present invention generally relates to utility systems, and moreparticularly to monitoring and inspecting utility system components.

BACKGROUND

The North American power grid has been characterized by the SmithsonianInstitution as the largest machine ever built by mankind. The size,geographic diversity, environmental diversity, and the multitude ofcomponents that comprise the power grid presents unique challenges inthe rapid and efficient upgrading the system with diverse newtechnologies that realize America's objective of improved power gridreliability and hardening. Accordingly, utility systems are an integralpart of modern day life. Unfortunately, components of these systems maybecome inoperable. For example, consider an electrical power substationthat is part of a power grid. Substations perform various functions suchas transforming voltage, connecting two or more transmissions lines,transferring power, and protecting the grid from short circuits andoverload currents. In many instances substation equipment is susceptibleto damage, which may result in power outages throughout the grid. Poweroutages decrease customer satisfaction and damaged substation equipmentincreases costs incurred by the utility provider.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The accompanying figures where like reference numerals refer toidentical or functionally similar elements throughout the separateviews, and which together with the detailed description below areincorporated in and form part of the specification, serve to furtherillustrate various embodiments and to explain various principles andadvantages all in accordance with the present disclosure, in which:

FIG. 1 is an illustrative example of a system for autonomousinspection/monitoring of components within areas of interest accordingto one embodiment of the present invention;

FIG. 2 is a block diagram illustrating one example of a mobile unmannedmonitoring device according to one embodiment of the present invention;

FIG. 3 is a block diagram illustrating one example of an informationprocessing system for managing autonomous inspection/monitoring ofcomponents within areas of interest according to one embodiment of thepresent invention;

FIG. 4 shows one example of area of interest data according to oneembodiment of the present invention;

FIG. 5 shows one example of monitoring device data according to oneembodiment of the present invention;

FIG. 6 shows one example of system component data according to oneembodiment of the present invention;

FIG. 7 shows one example of inspection paths assigned to different typesof mobile unmanned monitoring devices according to one embodiment of thepresent invention;

FIG. 8 shows one example of inspection path data according to oneembodiment of the present invention;

FIG. 9 shows one example of inspection results data according to oneembodiment of the present invention;

FIG. 10 shows one example of an autonomously generated work orderaccording to one embodiment of the present invention;

FIG. 11 is an illustrative example of an interactive map representing anarea of interest; mobile unmanned monitoring devices; and systemcomponents according to one embodiment of the present invention;

FIG. 12 is an operational flow diagram illustrating one example ofmanaging autonomous inspections of system components within areas ofinterest according to one embodiment of the present invention; and

FIG. 13 is a block diagram illustrating another example of aninformation processing system according to one embodiment of the presentinvention.

DETAILED DESCRIPTION

As required, detailed embodiments are disclosed herein; however, it isto be understood that the disclosed embodiments are merely examples andthat the systems and methods described below can be embodied in variousforms. Therefore, specific structural and functional details disclosedherein are not to be interpreted as limiting, but merely as a basis forthe claims and as a representative basis for teaching one skilled in theart to variously employ the disclosed subject matter in virtually anyappropriately detailed structure and function. Further, the terms andphrases used herein are not intended to be limiting, but rather, toprovide an understandable description.

The terms “a” or “an”, as used herein, are defined as one or more thanone. The term plurality, as used herein, is defined as two or more thantwo. The term another, as used herein, is defined as at least a secondor more. The terms “including” and “having”, as used herein, are definedas comprising (i.e., open language). The term “coupled”, as used herein,is defined as “connected”, although not necessarily directly, and notnecessarily mechanically. The term “configured to” describes hardware,software or a combination of hardware and software that is adapted to,set up, arranged, built, composed, constructed, designed or that has anycombination of these characteristics to carry out a given function. Theterm “adapted to” describes hardware, software or a combination ofhardware and software that is capable of, able to accommodate, to make,or that is suitable to carry out a given function.

The below described systems and methods provide for the remoteautonomous inspection of system components within areas of interest(AOIs) utilizing autonomous monitoring devices, and further facilitatesthe autonomous generation of work orders for rapid deployment of repaircrews. In some embodiments, AOIs are geographical areas comprisingutility system components. However, embodiments of the present inventionare not limited to utility systems. Components of a utility system maywear down, become damaged, or become inoperable. Depending on thegeographical location of these components; current weather conditions;types of damage or operational issues; and/or the like it may bedifficult to detect, locate, and remedy the issues within an acceptableamount of time. This may result in increased downtime of the systemcomponent(s), which decreases customer satisfaction and increases costsincurred by the utility provider.

Conventional utility system inspection/monitoring mechanisms generallyinvolve dispatching work crews to inspect and identify any worn down ordamaged component(s), the extent of damage, cause of damage, etc. Theseconventional mechanisms are problematic because they increase thedowntime of the system component, increase outages experienced by thecustomer, increase expenses incurred by the utility provider, etc. Forexample, it takes times for a crew to reach a site to assess damage,identify inoperable components, and receive repair components. Inaddition, the work crew may need to operate in dangerous environmentalconditions to identify and repair the problematic components. Also,conventional work orders usually do not provide very detailedinformation or require users to access multiple menus/pages to drilldown to information of interest. This can be problematic when viewingwork orders on portable electronic devices such as mobile phones,tablets, etc.

Embodiments of the present invention overcome the above problems byimplementing an autonomous system across one or more informationprocessing systems. The system autonomously manages mobile unmannedmonitoring devices for obtaining inspection data associated with one ormore system components within AOIs, and further for autonomouslygenerating work orders based on the inspection data. As will bediscussed in greater detail below, the system programs at least onemobile unmanned monitoring device to autonomously monitor at least onesystem component within an area of interest. The system communicationswith the at least one mobile unmanned monitoring device and receivesinspection data for the at least one system component that was generatedby the at least one mobile unmanned monitoring device. The systemutilizes one or more machine learning mechanisms to process theinspection data. Based on this processing, the system determines acurrent operational state of the at least one system component. Then,the system autonomously generates a work order based on the operationalstate. The work order comprises a plurality of components addressing thecurrent operational state of the at least one system component. Thesystem autonomously provisions one or more of the plurality ofcomponents for the work order.

Embodiments of the present invention allow for system components, suchas utility systems components, to be autonomously monitored andinspected for real-time or near real-time detection and identificationof problems experienced by the components. In addition, the autonomoussystem is able to process large amounts of data of different typescaptured by mobile unmanned monitoring devices, which allows for moreefficient and accurate detection of damaged system components whencompared to conventional systems. Work orders may be autonomouslygenerated and the required parts, equipment, and work crews identifiedwithin the work order may be autonomously provisioned to provide anadvantageous improvement in response time when compared to conventionalsystems. The above allows for system/component down time, customerdissatisfaction, and utility provide expenses to be greatly decreasedsince work crews do not need to be dispatched to diagnose the problem.In addition, embodiments of the present invention generate aninteractive map allowing work crew members to see important work order,system component, and inspection data information on displays of, forexample, mobile phones and tablets without having to parse throughmultiple, windows, menus etc.

FIG. 1 shows one example of an operating environment 100 for remoteautonomous inspection of utility system components. In one embodiment,the operating environment 100 may comprise one or more AOIs 102,monitoring devices 104 to 112, information processing systems 114, userdevices 116, networks 118, and/or the like. The AOI(s) 102 may be adefined geographical area comprising one or more geographical featuresand components of a utility system situated at various locations withinthe AOI 102.

Examples of geographical features includes rivers, streams, hills,cliffs, mountains, trees, boulders, and/or the like. Examples of utilitysystems include power grid systems (e.g., fossil fuel based,solar-based, wind-based, nuclear-based generation, transmission and/ordistribution subsystems), telephone systems (landline and wireless),water systems, gas systems, and oil systems. Each of these differenttypes of utility systems may have multiple types of subsystems. Forexample, an electric power delivery system generally comprises ageneration subsystem, a transmission subsystem, and a distributionsubsystem. Each of these of these subsystems performs one or morespecific functions and comprise multiple components. For example, thedistribution subsystem of an electric power system comprises substationswhere each substation performs various functions for a power grid suchas transforming voltage, connecting transmissions lines, transferringpower, and protecting the grid from short circuits and overloadcurrents, and/or the like. Components of a substation include, but arenot limited to, incoming and outgoing power lines, transformers,disconnect switches, circuit breakers, arresters, etc. Othernon-limiting examples of utility system components include utilitypoles, transmissions lines, solar panels, cooling towers, pipelines,and/or the like.

In the example shown in FIG. 1 , the AOIs 102 includes an electricalpower “grid” that is used to provide electrical power to consumerpremises 136. Area 102 may contain a multitude of individual oroverlapping AOIs. The example shown in FIG. 1 depicts a number ofexample power generation components 120. Illustrated are a combinedcycle gas generator 122, a solar array farm 124, and a wind farm 126AOIs. In further examples, operational contexts are able to include onepower generation component, multiple collocated power generationcomponents, power generation components that are physically separatedand supply a common electrical power transmission or distributionsystem, any one or more power generation components, or combinations ofthese. These power generation components are able to be of any suitabletype or design.

In this example, electrical power generated by one or more powergeneration components is provided to a power transmission system 128.The illustrated example depicts a transmission connection 130 thatcouples one or more sources within power generation components 120 tothe power transmission system 128. The transmission connection 130 andpower transmission system 128 AOIs in an example include suitablestep-up transformers and long-distance transmission lines to convey thegenerated electrical power to remote power distribution networks, otherelectrical power consumers, or both.

The illustrated power transmission system 128 provides electrical powerto one or more distribution systems including a substation 132,distribution lines 134 and premises 136. The substation 132 AOI mayinclude transformers, protection devices, and other components toprovide electrical power to a power distribution lines 134. The powerdistribution lines 134 delivers power produced by the generatingcomponents 124 to customer premises, such as the illustrated home 136.In general customer premises are coupled to the power distributionsystem 138 and are able to include any combination of residential,commercial or industrial buildings. FIG. 1 further shows the one or moremonitoring/inspection devices 104 to 112 placed at one or more locationswithin the AOIs 102. As will be discussed in greater detail below, themonitoring devices 104 to 112 are configured to remotely andautonomously inspect utility system components.

The monitoring devices 104 to 112, in one embodiment, may be unmannedmobile monitoring devices such as (but are not limited to) unmannedaerial vehicles (UAVs), drones, rovers, climbing robots, and/or the likehaving monitoring systems such as optical cameras, infrared sensors,LIDAR, RADAR, acoustic systems, and/or the like. In other embodiments,one or more of the monitoring devices 104 to 112 may be a fixed devicesuch as a camera. As will be discussed in greater detail below themonitoring devices 104 to 112 may autonomously monitor and inspectsystem components within an AOI 102.

FIG. 2 shows one non-limiting example of a monitoring device 200corresponding to the monitoring devices 104 to 112 of FIG. 1 . In thisexample, the monitoring device 200 comprises one or more processors 202,a monitoring unit 204, mobility controls 206, one or more storage units208, one or more power systems 210, one or more guidance systems 212,one or more wireless communication systems 214, and a monitoring system216. The processor(s) 202 may perform various computing functions forthe monitoring device 200. The monitoring unit 204 may control automatedmobility (e.g., flying, roving, climbing, etc.) operations of the device200; receive data from the information processing system 114 suchinspection path data and instructions indicating that the monitoringdevice 200 is to initiate mobility operations; managesmonitoring/inspection operations to be performed by the device 200 forone or more system components of the AOI 102; and/or the like.

In one embodiment, the monitoring unit 204 utilizes the monitoringsystem 216 and computer/machine learning mechanisms to autonomouslyidentify system components; determine a current operational state of thesystem components; determine any problems with and/or damage to thecomponents; and/or the like. The monitoring unit 204 may also controlautomated mobility operations of the device 200. For example, if thedevice 200 is a UAV the monitoring unit 204 (and/or processor 202) mayautonomously control the various systems and mobilitycontrols/components that enable the monitoring device 200 to traverse aninspection path. The monitoring unit 204 may be part of the processor202, is the processor 202, or is a separate processor. The monitoringunit 204 is discussed in greater detail below.

The mobility controls 206 comprise various mechanisms and componentssuch as propellers, tracks, motors, gyroscopes, accelerometers, and/orthe like that enable the monitoring device 200 to take flight, rove,climb, and/or the like. The mobility controls 206 are autonomouslymanaged and controlled by the monitoring unit 204 and/or processor 202.The storage unit(s) 208 includes random-access memory, cache, solidstate drives, hard drives, and/or the like. In one embodiment, thestorage unit(s) 208 comprises inspection path data 218, inspection data220, and/or the like. The inspection path data 218, in some embodiments,is received by the monitoring unit 204 from the information processingsystem 114 and/or is autonomously generated by the monitoring unit 204.The inspection path data 218 includes, for example, predefined and/orautonomously generated coordinates that form a path be traversed by themonitoring device 200 for inspecting/monitoring one or more systemcomponents within an AOI 102. The inspection path data 218 includes mayalso include altitude data and speed data that indicate the altitude andspeed at which the monitoring device 200 is to traverse one or moreportions of the inspection path. The inspection path data 218 mayfurther include data indicating specific angles at which the monitoringdevice 200 is to position itself relative to a given system componentfor capturing inspection data 220.

The inspection path data 218 may be stored at the monitoring device 200and/or at the information processing system 114. In this embodiment, themonitoring unit 204 of the device 200 may receive an instruction fromthe information processing system 114 indicating that the device 200 isto initiate mobility operations (e.g., initiate flight, roving,climbing, etc.) along with the identifier of the inspection path to betaken. The monitoring unit 204 may analyze the inspection path data 218to identify the inspection path corresponding to the receivedidentifier. In another embodiment, the monitoring unit 204 autonomouslydetermines which inspection path data 218 to follow based on parameterssuch as day, time, expected weather, and/or the like.

The power system(s) 210 provides power to the monitoring device 200 andits components. The power system(s) 210 may include batteries,photovoltaic components, fuel, and/or the like. The guidance system 212,in one embodiment, comprises components such as a Global PositioningSystem (GPS) tracking system, accelerometers, gyroscopes, magnetometers,collision avoidance components (e.g., LIDAR, RADAR, etc.), and/or thelike. The GPS tracking system may be utilized to plot trajectories ofthe device 200 and determine the location, speed, heading, and altitudeof the device 200. The accelerometer(s) may also be utilized todetermine the speed of the device, while the magnetometer(s) may beutilized to determine the device's heading. The gyroscope enables thedevice 200 to correct its orientation with respect to the ground. TheGPS tracking system may utilize one or more of the location, speed,heading, and altitude data to adjust the course of the device 200. Thecollision avoidance components enable the device to detect obstacles inits path and adjust its location, speed, heading, and/or altitudeaccordingly.

The wireless communication system 214 comprises components such as Wi-Fibased transmitters/receivers, cellular-based transmitter/receivers, etc.that enable the device 200 to send and receive secured and/or unsecuredwireless communications. The wireless communication system 214 may alsoinclude wired network components that may be utilized to transmit datawhile the device 200 is docked at a docking station, recharging station,and/or the like. The monitoring system 216, in one embodiment, comprisesone or more optical cameras, infrared sensors, LIDAR, RADAR, acousticsystems, and/or the like that capture their respective data typesassociated with system components within an AOI 102. The captured datais stored as inspection data 220.

FIG. 3 shows one non-limiting example of the information processingsystem 114. The information processing system 114 may include one ormore processors 302; one or more storage devices 304;networking/communication components 306; and an inspection manager 308comprising a repair manager 310. In one embodiment, the storagedevice(s) 304 may store various types of data such as AOI data 312,monitoring device data 314, utility system component data 316,inspection path data 318, inspection data 320, work order data 322,parts data 324, equipment and tool data 326, work crew data 328,interactive map data 330, training data 332, repair data 334, weatherdata 336, inspection results data 338 and/or the like. It should benoted that although FIG. 3 shows the various types of data 312 to 336residing within the storage device(s) 304, one or more of these datasetsmay reside outside of the storage device(s) 304 on one or more remoteinformation processing systems. It should also be noted that one or moreof the information processing system components may be distributedacross multiple information processing systems. The components of theinformation processing system 114 are discussed in greater detail below.In some embodiments, the inspection manager 308 performs one or moreoperations performed by the monitoring unit 204 of the monitoringdevices 104 to 112, and vice versa.

In one embodiment, the inspection manager 308 may program the monitoringdevices 104 to 112 with one or more inspection paths for performinginspection operations with respect to system components within the AOI102. In other embodiments, the monitoring unit 204 may program themonitoring device 104 with one or more inspection paths. The inspectionpaths may be predefined and/or autonomously generated by the inspectionmanager 308. The inspection paths are stored within the storagedevice(s) 304 of the information processing system 114 as inspectionpath data 318. In an embodiment where the inspection manager 308autonomously generates the inspection paths, the inspection manager 308analyzes the AOI data 312, monitoring device data 314, and utilitysystem component data 316 to determine a given inspection path for agiven monitoring device 104 to perform inspection operations for one ormore system component(s).

AOI data 312 comprises data such as (but not limited to) thegeographical type of the AOI, geographical features within the AOI,geographical size or boundaries of the AOI, elevation of the AOI,historical weather of the AOI, local and/or migratory wildlife data forthe AOI, and/or the like. The inspection manager 308 may obtain AOI data312 for a given AOI 102 in different ways. For example, the inspectionmanager 308 may utilize one or more of the networking components 306 toestablish a communication link with a remote information processingsystem(s) (not shown) via the network 118, where the communication linkmay be secure or unsecure. In this example, the remote informationprocessing system stores AOI data for one or more utility systems. Uponestablishing the communication link, the inspection manager 308 maydownload the AOI data 312 stored at the remote information processingsystem and store this data as local AOI data 312 in the one or morestorage devices 304. In other embodiments, the inspection manager 308does not download the remotely stored AOI data, but accesses andprocesses this data directly on the remote information processingsystem. Alternatively, the remote information processing system may pushits AOI data to the inspection manager 308 at one or more predefinedintervals and/or upon new AOI data being obtained by the remoteinformation processing system.

In some embodiments, the AOI data 312 obtained from the remoteinformation processing system comprises data for all AOIs associatedwith one or more entities (e.g., utility providers) utilizing theinspection manager 308. In other embodiments, the inspection manager 308obtains the remote AOI data on an as needed basis. For example, when theinspection manager 308 determines an AOI 102 requires inspectionoperations the inspection manager 308 only obtains AOI data for thespecific AOI 102 (and possibly related AOIs as well).

FIG. 4 shows various examples of AOI data 312. In the example shown inFIG. 4 , each row 402, 404, 406 in the table 500 corresponds to AOI datafor a given AOI and is referred to herein as an “AOI profile”. In thisexample, each column within the table 400 stores a different type ofdata. It should be noted that embodiments of the present invention arenot limited to the types of data shown in the columns of FIG. 4 . Also,one or more of the columns shown in FIG. 4 may be removed and/oradditional columns having different types of data may be added. Itshould also be noted that AOI profiles for different AOIs are notrequired to be stored in a single table and may be stored separate fromeach other.

In the example shown in FIG. 4 the table 400 comprises a first column408 entitled “AOI ID”; a second column 410 entitled “Location”; a thirdcolumn 412 entitled “Size”; a fourth column 414 entitled “Terrain Type”;a fifth column 416 entitled “Elevation”; a sixth column 418 entitled“Features”; and a seventh column 420 entitled “Historical Weather”. The“AOI ID” column 408 comprises entries 422 such as a unique identifierthat uniquely identifying each AOI and its profile in the table 400. The“Location” column 410 comprises entries 424 with data identifying thelocation of the AOI associated with the AOI profile. One example oflocation data includes a range of longitude and latitude coordinatesdefining the area encompassed by the AOI. The “Size” 412 columncomprises entries 426 indicating the geographical size of the AOI. The“Terrain Type” column 414 comprises entries 428 indicating the type ofterrain associated with AOI. For example, the entries may indicate theterrain type as “Hill”, “Desert”, “Mountain”, “Open”, etc. The“Elevation” column 416 comprises entries 430 indicating the elevation ofthe AOI.

The “Features” column 418 comprises entries 432 identifying geographicalfeatures and (optionally) their locations within the AOI. For example, afeature entry under this column may indicate the AOI has a river/stream,mountain, cluster of trees, boulders, and/or the like at specificlocations within the AOI. In another example, a feature entry mayindicate that the ground within the AOI is comprised of gravel, grass,cement, and/or the like. The “Historical Weather” column 420 comprisesentries 434 having historical weather data such as weather patterns forthe AOI. For example, the entries under this column may indicate thedaily, weekly, monthly, and/or yearly average temperatures, humiditylevels, wind speeds, rainfall, snowfall, UV levels, and/or the like.

Monitoring device data 314 for a given monitoring device comprises datasuch as (but not limited to) device type, sensor data, power source(s),communication capabilities, environmental protection, mobilitycapabilities, operational range/time(s), and/or the like. The inspectionmanager 308 may obtain monitoring device data for a given AOI similar tothe methods discussed above with respect to the AOI data 312. FIG. 5shows various examples of monitoring device data 314. In the exampleshown in FIG. 5 , each row 502, 504, 506 in the table 500 corresponds tomonitoring device data for a given set of monitoring devices; anindividual monitoring device; and/or monitoring device accessories suchas refueling/recharging docking systems and weather protectionenclosures. Each row 502, 504, 506 may be referred to herein as an“monitoring device profile”. In this example, each column within thetable 500 stores a different type of data. It should be noted thatembodiments of the present invention are not limited to the types ofdata shown in the columns of FIG. 5 . Also, one or more of the columnsshown in FIG. 5 may be removed and/or additional columns havingdifferent types of data may be added. It should also be noted thatmonitoring device profiles for different monitoring devices are notrequired to be stored in a single table and may be stored separate fromeach other.

In the example shown in FIG. 5 the table 500 comprises a first column508 entitled “Device ID”; a second column 510 entitled “Device Type”; athird column 512 entitled “Sensor/Feature Data”; a fourth column 514entitled “Power Source(s)”; a fifth column 516 entitled “Comm”; a sixthcolumn 518 entitled “Protection”; a seventh column 520 entitled“Mobility”; an eighth column 522 entitled “Op Features”; a ninth column524 entitled “Op Time”; and a tenth column 526 entitled “Op Costs”. The“Device ID” column 508 comprises entries 528 comprise a uniqueidentifier for the device associated with the monitoring device profile.It should be noted that in some embodiments, each row in the table is amonitoring device profile for a group of identical devices such as agiven product. For example, a monitoring device profile may represent agiven product such as a specific UAV model. In this embodiment, theidentifier uniquely identifies the product as a whole. In otherembodiments, a monitoring device profile represents an individual devicewhere multiple identical device each of their own monitoring deviceprofile. In this embodiment, the identifier uniquely identifies theindividual device.

The “Device Type” column 510 comprises entries 530 indicating the devicetype of the monitoring device(s) associated with the device profile.Examples of device types include (but are not limited to) UAV, rover,climbing robot, camera, and/or the like. The “Sensor/Feature Data”column 512 comprises entries 532 identifying and/or describing thesensors/features that are implemented on the monitoring device(s). Forexample, these entries may indicate whether the device(s) has a GPSsystem; accelerometer; a barometer; a weather sensor; an optical imagingsystem for capturing photographs and/or video; the type of image sensorutilized by the system (e.g., visible light sensor, infrared sensor,etc.); the resolution of the system; focal length of lens; zoomcapabilities; and/or the like. The sensor data entries may also indicateif the device has a thermal sensor; ion sensor; plasma sensor; audiosensor; and/or the like, and further identify the operating capabilitiesof these sensors.

The “Power Source(s)” column 514 comprises entries 534 identifying thetypes of power sources utilized by the device and their operatingcharacteristics. For example, a power source entry may indicate that themonitoring device comprises a rechargeable or disposable(non-chargeable) battery; number of batteries; whether a rechargeablemay be charged using solar or non-solar mechanisms; battery chemistry;battery voltage; battery capacity; battery power; and/or the like. The“Communication” column 516 comprises entries 536 identifying thecommunication capabilities of the device. For example, a communicationentry may indicate whether the device has wired and/or wirelesscommunication abilities; the communication standards/networks supportedby the device; security protocols implemented by the device; and/or thelike.

The “Protection” column 518 comprises entries 538 indicating the type ofenvironmental protection that is utilized by the device. For example,these entries may indicate the International Protection (IP) Markingcode of the device; degree of protection against electromagnetic pulses;degree of protection against drops, bumps, and falls; and/or the like.The “Mobility” column 520 comprises entries 540 indicating the mobilitycapabilities of the device. For example, a mobility entry may indicatewhether the device is fixed or mobile; identify a mobility modality suchas flight, ground traversal, climbing, and/or the like; if the device isa camera whether it can be panned and/or tilted; and/or the like.

The “Operating Features” column 522 comprises entries 542 indicatingspecific features of the device. For example, an operating feature entrymay identify the roving, flight, or climbing speed of the device; thenumber of wheels or propellers; the altitude limit of the device;whether the device has a return to base feature when batter levels arelow; and/or the like. The “Op Time/Range” column 524 comprises entries544 indicating the operating time and/or range of each device of thedevice before recharging or refueling is needed. The “Op Costs” column526 comprises entries 546 indicating the costs associated with operatingthe device. For example, these entries may indicate the purchase cost ofthe device; prices for replacement parts; average cost to operate thedevice on a daily, monthly, and/or yearly basis; and/or the like. Theaverage operating cost may take into consideration factors such asexpected repairs or parts replacement, fuel or electricity costs, and/orthe like.

System component data 316 comprises data such as (but not limited to) aunique identifier of the component; part number of the component;location of the component; function of the component; configurationdata; and/or the like. The inspection manager 308 may obtain systemcomponent data 316 for a given AOI 102 utilizing methods similar tothose discussed above with respect to the AOI data 312.

FIG. 6 shows various examples of system component data 316. In theexample shown in FIG. 6 , each row 602, 604, 606 in the table 600corresponds to system component data for system components locatedwithin AOIs, and is referred to herein as an “system component profile”.In this example, each column within the table 600 stores a differenttype of data. It should be noted that embodiments of the presentinvention are not limited to the types of data shown in the columns ofFIG. 6 , and one or more columns shown in FIG. 6 may be removed and/oradditional columns having different types of data may be added. Itshould also be noted that system component profiles for different systemcomponents are not required to be stored in a single table and may bestored separate from each other. In some embodiments, the systemcomponent data 316 may be part of the AOI data 312.

In the example shown in FIG. 6 the table 600 comprises a first column608 entitled “Component ID”; a second column 610 entitled “ComponentType”; a third column 310 entitled “AOI”; a third column 614 entitled“Part Number”; a fourth column 616 entitled “Location”; and a fifthcolumn 618 entitled “Function”. The “Component ID” column 608 comprisesentries 620 that include a unique identifier for the componentassociated with the system component profile. The identifier may be aserial number or any other identifier that uniquely identifies thesystem component. The “Component Type” column 610 comprises entries 622indicating the type of system component (e.g., transformer, solar panel,wind turbine, etc.) associated profile. The “AOI” column 612 comprisesentries 624 with data identifying the AOI where the given systemcomponent location resides. The AOI entries may comprise a pointer tothe corresponding AOI profile within the AOI data 210 and/or a uniqueidentifier of the AOI. In some embodiments, an AOI profile for a givenAOI may comprise an entry having the unique identifiers of the systemcomponents residing within the AOI and/or pointers to the correspondingsystem component profiles.

The “Part Number” column 614 comprises entries 626 indicating the partnumber/model of the system component. The “Location” column 616comprises entries 628 identifying the location of the system componentwithin the AOI. For example, location entries may compriselatitude/longitude coordinates of the component; altitude data; and/orthe like. The “Function” column 618 comprises entries 630identifying/describing the functions and features of the component.

When the inspection manager 308 determines a monitoring device 104requires inspection path data 318, the inspection manager 308 utilizesone or more of the AOI data 312, monitoring device data 314, and utilitysystem component data 316 to determine a given inspection path for agiven monitoring device 104. The inspection manager 308 may determinethat a monitoring device 104 requires inspection path data 318 based ona communication received from the monitoring device 104; a communicationreceived from a remote information processing system; a determinationmade by the inspection manager 308 that the monitoring device 104 is notcurrently associated with an inspection path or its current path needsto be updated; obstructions/debris identified within a currentinspection path of the device; and/or the like. In some embodiments, theinspection manager 308 may identify obstructions/debris based onprocessing inspection data received from the monitoring device 104(and/or a different monitoring device); receiving a communication fromthe monitoring device 104 (and/or a different monitoring device) basedon the monitoring device(s) 104 processing its inspection data anddetermining that an obstruction/debris is it its inspection path; and/orthe like.

The inspection manager 308 may analyze the AOI data 312, the monitoringdevice data, and/or the utility system component data 316 to determineinformation such as the AOI in which the device 104 is located;geographical features of the AOI; the location within the AOI 102 atwhich the device 104 is located; the device's operational capabilities(e.g., range, battery life, mobility capabilities, inspectioncapabilities, etc.); the system components within the AOI 102; thelocation of the components within the AOI; system componentconfiguration; and/or the like. The inspection manager 308 analyzes theobtained data and autonomously generates one or more inspection pathsfor the monitoring device 104 and stores the path as inspection pathdata 318.

For example, the inspection manager 308 may determine that theinspection/monitoring device 104 is a UAV located at position P_1 and isto monitor system component located at P_N at and having a height ofH_1. The inspection manager 308 may further determine that monitoringdevice 104 has flight capabilities, a battery capacity of C and anoperational range of R. The inspection manager 308 also determines thatthe AOI comprises a cluster of trees near the system component atposition P_2. Taking this data into consideration, the inspectionmanager 308 autonomously generates one or more flight paths for themonitoring device such that the device avoids the cluster of trees andis able to perform one or more inspection operations with respect to thesystem component while being able to return to its home base (or atleast a recharging station) prior to depleting its power/energysource(s). The inspection manager 308 may utilize one or more machinelearning mechanisms for generating an inspection path. A discussion onmachine learning mechanisms is provided in greater detail below. In someembodiments, the monitoring unit 208 may perform the operationsdiscussed herein with respect to selecting and/or autonomouslygenerating an inspection path for its monitoring device 104 to traverse.

FIG. 7 shows one example of inspections paths defined for monitoringdevices. In this example, an AOI 702 comprises transmissions lines 704and substation components 706. A first monitoring device 708 has beenselected to monitor the transmission lines 704 and a second monitoringdevice 710 has been selected to monitor the substation components 706.The first monitoring device 707 has been assigned a first inspectionpath 712, while the second monitoring device 710 has been assigned asecond inspection 714. It should be noted that a single monitoringdevice may be assigned multiple inspection paths. As will be discussedin greater detail below, the monitoring devices 708, 710 traverse theirinspection paths 712, 714 to perform one or more inspection operationswith respect to the system components 704, 706.

In some embodiments, there may be multiple monitoring devices 104 to 112located within a given AOI 102. In these embodiments the AOI data 312,the monitoring device data, and/or the utility system component data 316may indicate which device(s) is to monitor a given system component(s).The inspection manager 308 may also determine which device is to monitora given system component based on its distance from the systemcomponent, the device's operational capabilities, geographical featuresof the AOI 102, configuration of the system component; and/or the like.

For example, the AOI of FIG. 7 comprises a first monitoring device 708and a second monitoring device 710. Based on the monitoring device data314, the inspection manager 308 determines that the first monitoringdevice 708 is a UAV and the second monitoring device 710 is a rover. Themonitoring device also determines that the AOI 102 comprisestransmissions lines 704 and substation components 706 based on the AOIdata 312 and/or the system component data 316. Based on, for example,the operational capabilities of each monitoring device 708, 710identified within the device data 314 the inspection manager 308 selectsthe first monitoring device 708 to inspect the transmission lines 704and the second monitoring device 710 to inspect the substationcomponents 706. It should be noted that, in some embodiments, themonitoring unit 204 of a monitoring device 104 may perform theoperations discussed above with respect to the inspection paths.

Once the inspection manager 308 has selected and/or generated aninspection path for a given monitoring device 104, the inspectionmanager 308 stores the path as inspection path data 318. FIG. 8 showsvarious examples of inspection path data represented as a table 800. Inthe example shown in FIG. 8 , each row 802 to 808 in the table 800corresponds to an inspection path. It should be noted that in otherembodiments, each inspection path 802 to 808 is stored separate from oneanother. The table 800 comprises a plurality of columns, each storing adifferent set of information. In this example, the table 800 comprises afirst column 810 entitled “Inspection Path ID”; a second column 812entitled “Device ID”; a third column 814 entitled “Coordinate Data”; afourth column 816 entitled “Altitude Data”; a fifth column 818 entitled“Speed Data”; a sixth column 820 entitled “Temporal Data”; and a seventhcolumn 822 entitled “Inspection Angle(s)”. It should be noted that theinspection path data 318 is not limited to the items shown in FIG. 8 asone or columns may be removed or additional columns added.

The “Inspection Path ID” column 810 comprises entries 824 uniquelyidentifying each inspection path in the inspection path data. The“Device ID” column 812 comprises entries 826 identifying the monitoringdevice 104 associated with the inspection path. The entries 826 mayinclude the unique ID associated with the monitoring device; a pointerto the monitoring device profile associated with the device; and/or thelike.

The “Coordinate Data” column 814 comprises entries 828 with coordinatedata, which may be in three-dimensional space, defining a path andpattern to be traversed. Two or more of the inspection paths may havedifferent traversal patterns or all inspection paths may have the sametraversal pattern. In one embodiment, the coordinates of an inspectionpath are defined such that the monitoring device avoids colliding withany of the system components and other monitoring devices. In addition,two or more inspection paths may have coordinates that overlap with eachother.

The “Altitude Data” column 816 comprises entries 830 having altitudedata for the corresponding inspection path. For example, the altitudedata may define a given altitude a monitoring device 104 is to fly atwhile traversing the corresponding inspection path. In some embodiments,the altitude data may include different altitudes for different portionsof the inspection path. The different altitudes may be time-based and/orcoordinate-based. The “Speed Data” column 818 comprises entries 832having speed data for the corresponding inspection path. For example,the speed data may define a given speed the monitoring device 104 is tofly, rove, climb, and/or the like while traversing the inspection path.In some embodiments, the speed data may include different speeds fordifferent portions of the inspection path. The different speeds may betime-based, altitude-based, and/or coordinate-based. The inspection pathdata 318 may also comprise additional information such as the time/daythe monitoring device is to initiate traversal of an inspection path,time/day the monitoring device is to utilize the inspection path. Forexample, a monitoring device may be assigned different inspection pathsbased for different periods of time, expected weather patterns, and/orthe like.

The “Temporal Data” column 820 comprises entries 834 indicating at whenthe device is to traverse the flight path. For example, these entriesmay identify one or more days, one or more times, and/or the like thatthe device is to traverse the associated flight path. The “InspectionAngle(s)” column 822 comprises entries 836 indicating one or more anglesat which a monitoring device 104 is to position itself relative to agiven system component for capturing inspection data 220. It should benoted that the inspection path data may be dynamically updated by theinspection manager 308 and/or monitoring unit 204 as the monitoringdevice 104 is traversing the path. The inspection path data may also beupdated while the monitoring device 104 is docked at a docking stationor a refueling/recharging station.

In one embodiment, the inspection manager 308 establishes acommunication link with the monitoring device 104 and transmits theinspection path(s) to the device 104. The monitoring device 104 storesthe inspection path within a storage unit 208 as inspection path data218. When the monitoring unit 204 of the monitoring device 104determines that inspection operations are to be performed, themonitoring unit 204 initiates traversal of one or more inspection pathsbased on the inspection path data 218. For example, the monitoring unit204 may receive a signal from the information processing system 114instructing the monitoring unit 204 to perform the inspectionoperations. In another example, the monitoring unit 204 may havepreviously received data from the information processing system 114identifying the day and times the monitoring device 104 is to performinspection operations with respect to system components. This data maybe transmitted by the information processing system 114 as part ofinspection path data, separate from the inspection path data, and/or thelike.

In another embodiment, the monitoring unit 204 may dynamically determinewhen an inspection should be performed. For example, the monitoring unit204 may utilize one or more sensors within the monitoring system 216 orreceive weather data 336 from the information processing system (oranother system) to determine that inclement weather is approaching, isoccurring, and/or has occurred. Upon a determination that inclementweather is approaching or is expected, the monitoring unit 204 mayautonomously operate the device 104 to perform an inspection toestablish an operational state of the system component prior to theinclement weather. When the monitoring unit 204 determines the inclementweather has passed, the monitoring unit 204 may autonomously operate thedevice 104 to perform an inspection of the system component. Theinspection data captured prior to the inclement weather may be comparedagainst the inspection data captured after the inclement weather todetermine any changes in the operational state of the system component.In some embodiments, the inspection manager 308 may perform the aboveoperations as well.

In some instances, the monitoring device 104 may not be scheduled toperform an inspection for a period of time greater than a giventhreshold after inclement weather has occurred. In this situation, whenthe monitoring unit 204 determines that a weather event has occurred themonitoring unit 204 dynamically adjusts its inspection schedule toperform an inspection earlier than its schedule indicated. For example,the monitoring device 104 may autonomously operate the monitoring device104 as soon as it detects the weather even has passed. This allows forany problems with system components to be identified and resolved assoon as possible. It should be noted that the inspection manager 308 mayalso perform the above operations as well.

As the monitoring device 104 traverses an inspection path(s), the device104 performs inspection operations with respect to one or more systemcomponents within an AOI. The monitoring device 104 utilizes itsmonitoring system 216 to perform the inspection operations. As discussedabove, the monitoring system 216 comprises one or more optical cameras,infrared sensors, LIDAR, RADAR, acoustic systems, and/or the like thatcapture their respective data types associated with system components.As the system component(s) comes into range of the monitoring system216, the monitoring system 216 captures and records inspection data 218associated with the system component. For example, the monitoring system216 captures still images/frames or a video of the system component;audio associated with the system component; temperature measurements forthe system component; gas level measurements for the system component;and/or the like. The monitoring system 216 may also continuously captureinspection data 218 and not just when the system components come intorange of the monitoring system 216.

The monitoring unit 204 may store the captured data locally asinspection data 218 and/or transmit the data to the inspection manager308 at the information processing system 114. The data may also betransmitted to one or more of the user devices 116. The inspectionmanager 308 may store the received data as inspection data 320. Theinspection data 218 may be transmitted to the monitoring unit 204 and/orthe user devices 116 at one or more predefined intervals of time. Inaddition, the inspection data 218 may be transmitted/streamed to themonitoring unit 204 and/or the user devices 116 in real time. Theinformation processing system 114 and/or the user device 116 may thenpresent the inspection data to a user upon receiving the inspectiondata; at one or more intervals of time; upon request by a user; and/orthe like.

After the inspection manager 308 of the information processing system114 has received inspection data 320 from a monitoring device(s) 104,the inspection manager 308 processes the data to determine a currentoperational state of system components, determine whether systemcomponents are damaged or non-functioning, and/or the like. It should benoted that, at least in some embodiments, determining an operationalstate of a system component may encompass multiple operations such asdetermining if the component is operational; non-operational, operatingnormally (e.g., within expected parameters/thresholds); operatingabnormally (e.g., outside expected parameters/thresholds; determiningthat the component has been damaged, the type of damage, the parts ofthe component that have been damaged, the location of the damage, thecause of the damage, etc.; determining that the component is beingobstructed by debris, the type of debris, the location of the debris,etc.; and/or the like. It should be noted that the monitoring unit 204of a monitoring device 104 may also be configured to perform theseoperations as well.

In one embodiment, the inspection manager 308 utilizes one or moremachine-learning mechanisms to determine the operational state of thesystem component, any damaged associated with the component, and/or thelike. For example, the inspection manager 308 may utilize a deeplearning artificial neural network (DLANN) model trained to recognizesystem components, determine damage to the system components, determinethe type of damage, anticipate damage and/or abnormal operationconditions based on expected weather, and/or the like. It should benoted that other machine learning models and algorithms are applicableas well.

A DLANN model is generally comprised of a plurality of connected unitsreferred to as artificial neurons. Each unit is able to transmit asignal to another unit via a connection there between. A unit thatreceives a signal from another unit processes the signal and maytransmit its own signal to another unit based on the processed signal. Aunit may be associated with a state (e.g., 0≤x≤1) where both a unit anda connection may be associated with a weight that affects the strengthof the signal transmitted to another unit. The weight may vary duringthe learning process of the model. The model may comprise multiplelayers of connected units, where different layers perform differenttransformations on their inputs. The first layer acts as the initialinput (e.g., from the inputted data) to the model, where signals fromthis layer propagate to the final layer (e.g., identified solution). Theinitial layers of the model may detect specific characteristics of thetarget solution while inner layers may detect more abstractcharacteristics based on the output of the initial layers. The finallayers may then perform more a complex detection based on the outputinner layers to detect the target solution.

The DLANN model utilized by the inspection manager 308, in oneembodiment, is trained by providing training data 332 to the model as aninput. The model may be trained at the inspection manager 308 and/or atan external information processing system. In one embodiment, thetraining data 332 comprises different images of a target object such asa system component, a system component in a normal operating state, asystem component in an abnormal operating state (e.g., operating outsideof normal parameters/thresholds), one or more damaged portions of asystem component, obstructions and/or debris interfering with the systemcomponent, and/or the like. In one non-limiting example, an AOI 102comprises one or more transformers to be monitored/inspected. In thisexample, the training data 332 comprises different images of atransformer in a normal operating state, a transformer in an abnormaloperation state, a transformer with one or more portions being damaged,a transformer with trees or tree limbs interfering with the transformer,and/or the like.

In some embodiments, images comprising the target object(s) (e.g.,normal operating transformer, abnormal operating transformer, componentsof transformer having damage, specific types of debris interfering withtransformer components, etc.) to be detected by the inspection manager308 may be annotated with text and/or a bounding box using specificsoftware. It should be noted that other images of target objects notassociated with the environment may be used as training data as well. Itshould be also noted that embodiments of the present invention are notlimited to the environments and/or target objects discussed herein.

In some embodiments, the model comprises a convolution layer where asliding window is passed over each of the training images where eachportion of the training image is saved as a separate image. Each ofthese separate images for each original training file are then fed intothe model as training data. The result of this training step is an arraythat maps out which parts of the original image have a possible targetobject or part of a target object. Max pooling can then be used to downsample the array. The reduced array may then be used as input intoanother artificial neural network and the above processes can berepeated. The final artificial neural network (e.g., fully connectednetwork) determines whether a given image comprises a target object and,if so, which portion(s) of the image comprises the target object. Itshould be noted that the DLANN model may comprise multiple convolution,max-pooling, and full-connected layers. In addition, the trained DLANNmodel is able to tolerate shadows, variable image backgrounds, exposuresettings, and changing scene lighting, etc. A similar training processmay be utilized for other types of data such as audio, sensor readings,and/or the like.

Once the object detection model has been trained, the inspection manager308 implements the model as an object detector. For example, theinspection manager 308 is programmed to detect one or more specifictarget objects such as a normal operating solar panel, an abnormaloperating solar panel, specific components of the solar panel havingdamage, specific types of debris interfering with solar panelcomponents, etc. from inspection data 320 (e.g., captured images, audio,sensor data, etc.) captured by the monitoring device 104 to 112utilizing the object detector.

For example, as a monitoring device 104 is traversing an inspection pathits monitoring system 216 captures inspection data 220 such as (images,audio, sensor readings, location/position/time of device at which thedata was captured, etc.) of the AOI 102. In some embodiments, themonitoring system 216 continuously captures inspection data 220 while itis operating or traversing an inspection path. In other embodiments, themonitoring system 216 may be programmed with location data (e.g.,coordinates) of specific system components to be inspected. In thisembodiment, the monitoring unit 204 utilizes the guidance system 212 todetermine when the device 104 is within a threshold distance from thelocation of the system component(s) and activates the monitoring system216.

The monitoring unit 204 transmits its captured inspection data 220 tothe information processing system(s) 114, as discussed above. Theinspection manager 308 stores this data as local inspection data 320. Itshould be noted that inspection data 220 captured by a monitoring device104 may be stored on a different information processing system(s) andaccessed thereon by the inspection manager 308. The inspection manager308 processes/analyzes the inspection data 320 to determine if thereceived inspection data comprises a system component such astransmission lines. If the inspection manager 308 determines that theinspection data comprises or corresponds to a system component to beinspected the inspection manager 308 determines a current operationalstate of the system component based on the inspection data.

For example, if the inspection data 320 comprises images the inspectionmanager 308 processes these images utilizing its trained object detectorto determine if any of the images comprising the system component showthe component having any damage or debris. If not, the inspectionmanager 308 may determine the system component's operational state isnormal. However, if the inspection manager 308 determines the systemcomponent has been damaged or that debris is interfering with the systemcomponent the inspection manager 308 may determine that operationalstate of the system component is abnormal.

In some instances, the inspection manager 308 may be unable to determinea current operational state of the system component from the inspectiondata due to the angle at which the monitoring device captured an image.In one embodiment, the inspection manager 308 may communicate with themonitoring device 104 and instruct the device to capture an image fromone or more different angles. The inspection manager 308 may providespecific angles to the monitoring device and/or the monitoring unit 204of the device may determine additional angles at which to capture thedata. In another embodiment, the inspection manager 308 may select andinstruct one or more different monitoring devices to perform theadditional inspection operations. For example, a different monitoringdevice may be able to provide images from a different angle, providedifferent types of data, and/or the like.

In some embodiments, the inspection data 320 comprises data in additionto (or in lieu of) images. For example, the inspection data 320 mayinclude audio data, sensor reading data, and/or the like. As discussedabove, the object detector of the inspection manager 308 may also betrained utilizing this type of data as well. Therefore, the inspectionmanager 308 may also utilize this type of data to detect when a systemcomponent has been damaged and/or obstructed; the type of damage and/orobstruction; the location and/or part of the system component that hasbeen damaged and/or obstructed; and/or the like based not only on imagedata but also audio data, sensor reading data and/or the like. Theinspection manager 308 may utilize one or more types of data to detect acurrent operating condition of a system component and may utilize one ormore other types of data to perform a more granular analysis of thesystem component when damage or an abnormal operating condition has beendetected.

For example, when damage or an abnormal operating condition has beendetected utilizing a first type of inspection data, a second type ofinspection data may be utilized to determine the type of damage type,the location of the damage and/or the like. It should be noted that whena first set of inspection data comprising one or more inspection datatypes is utilized to detect a normal operating condition; abnormaloperating condition; damage type and/or the like the inspection manager308 may utilize a second inspection dataset comprising one or moredifferent inspection data types to confirm thesedetections/determinations. It should be noted that the monitoring unit204 of one or more monitoring devices 104 to 112 may perform theoperations of the inspection manager 308 discussed above. For example,the monitoring unit 204 may utilize one or more computer learningmechanisms similar to the inspection manager 308 to perform theinspection operations discussed above.

In some embodiments, the inspection manager 308 stores results ofprocessing the inspection data 320 as inspection results data 338. Theresults may be used to further train the machine learning components ofthe inspection manager 308. FIG. 9 shows various examples of inspectionresults data represented as a table 900. In the example shown in FIG. 9, each row 902 to 906 in the table 900 corresponds to an inspectionresults for a given system component. It should be noted that in otherembodiments, each inspection path 902 to 906 is stored separate from oneanother. It should also be noted that the inspection results data may bestored as part of other data such as system component data 316,inspection data 320, and/or the like. In addition, a given systemcomponent may have multiple entries within the table 900. The table 900comprises a plurality of columns, each storing a different set ofinformation. In this example, the table 900 comprises a first column 908entitled “Component ID”; a second column 910 entitled “AOI”; a thirdcolumn 912 entitled “Location”; a fourth column 914 entitled “Op State”;a fifth column 916 entitled “Damage Type”; a sixth column 918; entitled“Damaged Part”; a seventh column 920 entitled “Time”; and an eightcolumn 922 entitled “Weather”. It should be noted that the inspectionresults data 338 is not limited to the items shown in FIG. 9 as one orcolumns may be removed or additional columns added.

The “Component ID” column 908 comprises entries 924 that include aunique identifier for the component associated with the inspectionresults data. The identifier may be a serial number or any otheridentifier that uniquely identifies the system component and/or may be apointer to the system component profile associated with the systemcomponent. The “AOI” column 910 comprises entries 926 with dataidentifying the AOI where the given system component location resides.The AOI entries may comprise a pointer to the corresponding AOI profilewithin the AOI data 210 and/or a unique identifier of the AOI. In someembodiments, an AOI profile for a given AOI may comprise an entry havingthe unique identifiers of the system components residing within the AOIand/or pointers to the corresponding system component profiles.

The “Location” column 912 comprises entries 928 identifying the locationof the system component within the AOI. For example, these entries maycomprise latitude/longitude coordinates of the component; altitude data;and/or the like. The “Op State” column 914 comprises entries 930identifying the current operational state of the system component asdetermined by the inspection manager 316 as a result of processing theinspection data 320. For example, these entries may indicate that thesystem component is operating normal is operating abnormally, isnon-operational, is currently being obstructed by and/or interfered withdebris, and/or the like. The “Damage Type” column 916 comprises entries932 indicating the type of damage (if any) experienced by the systemcomponent. For example, these entries may indicate that a transformerhas exploded; a transmission line has become decoupled; a solar panelhas hail damage; and/or the like. The “Damaged Part” column 918comprises entries 934 indicating specific part or parts of the systemcomponent that has been damaged. The “Time” column 920 comprises entries936 indicating the time at which the inspection was performed. The“Weather” column 922 comprises entries 938 indicating the weather at thetime of inspection. The weather data may be utilized as historicalweather data for the inspection manager 308 when predicting potentialdamage to system components upon determining similar weather is expectedin the future.

When the inspection manager 308 detects that a system component isexperiencing a problem (e.g., a non-operational state, abnormaloperational state, has been damaged, has been obstructed and/or thelike) the repair manager 310 autonomously generates a work/repair orderfor the system component. In one embodiment, a work order may identifythe system component to be repaired/replaced; identifies the location ofthe system component, identifies the problem associated with the systemcomponent; identifies the cause of problem; identifies the partsrequired to repair or replace the system component; identifies the workcrew(s) to perform the repair; includes repair/replacement instructions;identifies current and/or expected weather at the location; and/or thelike.

In one embodiment, the repair manager 310 may utilize one or moremachine/computer learning mechanisms for autonomously generating a workorder. Examples of machine/computer learning mechanisms includesupervised learning, unsupervised learning, reinforcement learning,and/or the like. In some embodiments, the repair manager 310 implementsan artificial neural network (ANN) similar to the discussed above withrespect to the inspection manager 308. However, instead of detectingobjects within images the repair manager 310 generates work orders basedon the inspection results data 338. Work orders generated by the repairmanager 310 may be used to further train the machine learning componentsof the inspection manager 308 and/or the repair manager 310.

The machine/computer learning components of the repair manager 310 maybe trained utilizing historical repair data 334, repair manuals forsystem components, previously generated work orders, and/or the like.The historical repair data 334 may comprise data associated with aplurality of repair/replacement events. Each of these events isassociated with a given system component and comprises data such as suchas an identification of system component that was previously repaired;the type of damage that was repaired for the component; anidentification and description of the parts, tools, and their quantitiesused to repair the damage; procedures taken to repair the component;time taken to repair the component; the cause of the damage; the weatherconditions at the time of damage detection and at the time of repair;work crew identification; work crew details such as identifiers of crewmembers, crew member qualifications, etc.; and/or the like. In someembodiments, the historical repair data 334 may comprise works orderdata 322 from work orders previously generated by the repair manager 310and/or any other entity.

After the machine/computer learning components of the repair manager 310have been trained the repair manager 310 is able to autonomouslygenerate work orders for damaged/obstructed system components. Therepair manager 310 stores the work orders as work order data 322. Forexample, the repair manager 310 takes as input and processes theinspection results data 338. If the repair manager 310 determines fromthe inspection results data 338 that a system component is experiencinga problem, the repair manager 310 initiates one or more autonomous workorder generation processes.

Consider the example of inspection results data shown in FIG. 9 . Uponprocessing this data, the repair manager 310 determines the componenthaving the ID of CID_2 is experiencing a problem based on one or more ofthe Operational State entry, Damage Type entry, or the Damaged Partentry. The repair manager 310 processes the system component data 316 toidentify a profile comprising a component ID matching the component IDidentified within the inspection results data 338. In this example, therepair manager 310 determines that the system component experiencing aproblem is a Type_B system component (e.g., a transformer). It should benoted that the component type information may also be included withinthe inspection results data 338.

The repair manager 310 then autonomously generates a work order for thetransformer utilizing one or more of its machine learning components andstores this as work order data 322. For example, based on the systemcomponents and its attributes (e.g., type, location, configuration,etc.); damage and its attributes (e.g., type, location, cause, etc.);the specific parts of the system component that have been damaged; typeof debris obstructing the system component and/or surrounding areas;and/or the like the repair manager 310 determines the parts; tools;equipment; vehicles; work crew type; specific work crew member; and/orthe like required for repairing the transformer.

In some embodiments, the inspection results data 338 may not explicitlyidentify damaged parts of a system component, but may identify the causeof damage. For example, the type of damage may indicate that thetransformer was struck by lightning. Therefore, the repair manager 310may determine the parts that were most likely to be damaged by thisevent. Alternatively, the inspection results data 338 may explicitlyidentify the damaged parts. Based on the determination of these parts,the repair manager 310 is able to determine the tools and procedures forrepairing or replacing these parts based on its machine learningcomponents.

As discussed above, not only does the repair manager 310 determine theparts and tools required to repair system components but also determinesthe vehicles, equipment, and work crews required to repair the systemcomponent. For example, the repair manager 310 may process the AOI data312, device data 314, and system component data 316 and determine thatthe AOI 312 in which the system component is located comprises specificterrain that requires a specific type of repair vehicle for safe travel.The repair manager 310 may also utilize this data to determine that thesystem component is at a given location and has a given configurationthat requires a vehicle with a boom of a specific length. The repairmanager 310 may further determine that the particular damage or systemcomponent requires a specialized crew. The repair manager 310 utilizesthe above data to autonomously generate one or more work orders 322 forrepairing or replacing a system component(s).

In some embodiments, the repair manager 310 autonomously provisionsand/or assigns the required equipment, parts, tools, crews, etc. for agiven work order. For example, once the repair manager 310 hasdetermined which parts, equipment, tools, crews, etc. are required forservicing a system component the repair manager 310 may communicate withone or more information processing systems to provisions and/or assignsthese items to the job. In some embodiments, the repair manager 310 mayanalyze parts data 324 to determine if the required parts are available.If not, the repair manager 310 may autonomously order the requiredparts. In addition, the repair manager 310 may communicate with aninformation processing system at a parts warehouse, dispatch terminal,and/or the like to autonomously provision available parts to the currentjob. For example, the repair manager 310 may communicate with one ormore information processing systems managing the parts inventory andinstructs these systems to provision the parts for the current job.

The repair manager 310 may also perform similar operations with respectto the required equipment and tools. For example, the equipment and tooldata 326 may comprise data relating to the equipment and tools availableto work crews such as a unique identifier of the equipment/tools; typeof the equipment/tools; availability of the equipment/tools; location ofthe equipment/tools; features of the equipment/tools; and/or the like.The repair manager 310 processes this data to identify equipment andtools that satisfy the repair criteria determined by the repair manager310. When the repair manager 310 identifies equipment and tools thatsatisfy the repair criteria the repair manager 310 may autonomouslyprovision the equipment and tools for the job. For example, the repairmanager 310 may communicate with one or more information processingsystems managing the equipment/tool inventory and instructs thesesystems to provision the equipment/tools for the current job. Oneadvantage of the autonomous provisioning discussed above is that thetime to identify, retrieve, and prepare the required parts, equipment,and tools for a given work order is drastically reduced as compared toconventional systems.

The repair manager 310 may also process work crew data 328 to determineparticular crews that have attributes and availability that satisfycriteria required to perform the repairs on the system components. Forexample, the work crew data 328 may include a unique identifier for eachwork crew; a unique identifier for each individual that is part of thecrew; a current location and/or home base of the crew; a currentlocation of each individual crew member and/or the individual's homebase; the availability of the work crew and/or each crew member; thespecialties of the work crew and/or each individual crew member; contactinformation for each crew member; and/or the like. The repair manager310 processes the above data and selects one or more appropriate workcrews, makes substitutions of crew members, and/or the like.

Consider an example were the system component to be repaired is atransmission line. The repair manager 310 processes the work crew data328 to identify a work crew with a specialization in repairingtransmission lines. The repair manager 310 may utilize the work crewdata 328 to identify a work crew that has a home base closest to thetransmission line or to identify another crew if the first crew iscurrently not available. The repair manager 310 may further utilize thework crew data 328 to determine if each crew member of the identifiedwork crew is current available. If not, the repair manager 310 maysubstitute in another crew member based on his/her correspondinginformation within the work crew data 328. Once a crew and its membershave been selected, the repair manager 310 may utilize the contactinformation (e.g., mobile phone number, landline phone number, emailaddress, pager number, etc.) from the work crew data 328 to autonomouslysend one or more messages to the communication devices of the crewmembers. These messages at least inform the crew members that they arerequired to perform one or more jobs.

After the repair manager 310 has processed the inspection data 320,parts and equipment data 326, and/or work crew data 328 the repairmanager 310 autonomously generates one or more work orders 322. The workorder 322 may include data such as an identification of the systemcomponent to be repaired/replaced; the location of the system component;the problem associated with the system component; the cause of problem;the work crew(s) and its members assigned to perform the repair;repair/replacement instructions; equipment provisioned or required forthe repair; parts provisioned or required for the repair; toolsprovisioned or required for the repair; current and/or expected weatherat the location; and/or the like.

In one or more embodiments, the repair manager 310 establishes acommunication with one or more information processing systems, userdevices 116, and/or the like and transmits the generated work order(s)322 to the devices. FIG. 10 shows one example of a work order 322generated by the repair manager 310 being presented on a display 1002 ofa user device 116. A user device 116 may include cellular telephones,mobile phones, smart phones, in-vehicle devices; two-way pagers,wireless messaging devices, wearable computing devices, laptopcomputers, tablet computers, desktop computers, personal digitalassistants, a combination of these devices, and/or other similardevices.

In the example shown in FIG. 10 , the work order 322 comprises a firstrow 1004 uniquely identifying the work order. A second row 1006comprises the time and time associated with the work order 322. A thirdrow 1008 identifies the system component associated with the work order322, provides any details regarding the system component, and/or thelike. A fourth row 1010 provides location information associated withthe system component(s). A fifth row 1012 problems information regardingthe problem associated with system component(s) such as damage,obstruction, etc. The problem information may also include anyinformation determined by the inspection manager 308 such as location ofdamage, specific parts that are damaged, and/or the like.

A sixth row 1014 provides information identifying the cause of theproblem being experienced by the system component(s). A seventh row 1016identifies and provides information associated with the work crew(s)assigned to the work order. An eighth row 1018 provides instructions onhow to repair/replace the system component(s). A tenth row 1020identifies and provides information associated with theequipment/vehicles and tools required to repair/replace the systemcomponent(s). An eleventh row 1022 identifies and provides informationassociated with the parts required to repair/replace the systemcomponent(s). A twelfth row 1024 provides information regarding thepast, current, and/or expected weather at the repair site. It should benoted that the work order 322 is not limited to the configuration andthe information provided in FIG. 10 .

In some embodiments, one or more of the work order entries 1004 to 1024are selectable by a user to obtain additional information. For example,one or more items in the System Component(s) row 1008 may be selected bya user to view a schematic of the system component that is experiencinga problem. In one embodiment, when a user selects an item within SystemComponent(s) row 1008 the user device 116 establishes a connection withthe information processing system 114 (or another information processingsystem) to request the additional information. The informationprocessing system 114 obtains the requested information and transmits itto the user device 116 for presentation to the user. In anotherembodiment, the repair manager 110 packages this information with thework order 322 prior to transmitting the work order 322 to the userdevice 116.

In another example, one or more items within the Location row 1010 maybe selected to present an interactive map 330 associated with the systemcomponent(s) experiencing the problem. The interactive map 330 may beprovided to the user device similar to the system component datadiscussed above. In addition, the information processing system 114 mayact as a server for the interactive map 330, which is presented to auser through an application interface. As the user interacts with themap 330 the inspection manager 308 updates the maps and presentsinformation accordingly. It should be noted that the inspection manager308 is not limited to presenting the interactive map upon selection ofan item within the work order 322. The inspection manager 308 maypresent the map 330 to a user independent of the work order 322.

FIG. 11 shows one example of an interactive map 330 generated by theinspection manager 308. In this example, the interactive map 330displays the entire AOI comprising the system component associated withthe work order 322. The user is able to zoom in and zoom out on theinteractive map to obtain different granularities of informationassociated with the AOI, system components, topographical features,and/or the like. In the example of FIG. 11 , the interactive map 330comprises icons/widgets 1102 representing the AOI; system components1104 to 1112; icons/widgets 1114 to 1120 representing geographicalfeatures; and icons/widgets 1122, 1124, 1126 representing the monitoringdevices within the AOI. The inspection manager 308 generates andconfigures the icons/widgets or images representing these components tobe selectable by a user. In one embodiment, the system componentsassociated with the work order 322 are visually highlighted asillustrated by the dashed line 1128 surrounding the box 1114representing a transformer.

The user is able to select one or more of the icons/widget presentedwithin the interactive map 330. For example, FIG. 11 shows that when auser selects a geographical widget 1118, as represented by the arrow1130, the inspection manager 308 may configure the interactive map 330to display information 1132 such as an identifier of the features, thelocation of the topographical feature within the AOI; a type anddescription of the topographical feature; and/or the like. FIG. 11 alsoshows that when a system component widget 1114 is selected, asrepresented by the arrow 1134, the inspection manager may configure theinteractive map 1100 to display information such as the componentidentifier; component location; component description; and/or the like.If the selected system component widget 1114 is associated with a workorder 322, the interactive map 330 may also display information from thework order and/or inspection results data 338 such as identified damage,repair information, and/or the like. In addition, the work order 322 mayalso be presented to the user upon selection of a system componentwidget 1114 associated with the work order.

In one embodiment, when a user selects a system component widget 1114associated with work order 322 and/or selects displayed information suchas “damage”, “inspection data”, etc., the inspection manager 308 mayconfigure the map 330 to present the user with the images, audio, sensordata, and/or the like utilized by inspection manager 308 to determinethe component is experiencing a problem. This allows the crew members toreview and familiarize themselves with the issue they have been assignedto address. In another embodiment, the interactive map 330 allows a userto select one or more of the widgets 1122 associated with a monitoringdevice. When the inspection manager 308 determines a user has selected amonitoring device widgets 1122, the inspection manager 308 configuresthe map 330 to present information associated with the device such aslocation, assigned system components, location, type, features, etc.

In addition, the inspection manager 308 may configure the monitoringdevice associated with the selected widget 1122 to be controlled by theuser via his/her user device 116. In this embodiment, the map 330 may beconfigured to display a user interface to the user for controlling themonitoring device. This allows the user to control the device to obtainadditional inspection data that the user may need to repair/replace thesystem component. Any data captured monitoring device may be presentedto the user through the user interface in real time as the user iscontrolling the device. In one embodiment, commands selected by the userthrough the user interface for controlling the monitoring device aretransmitted to the inspection manager 308. The inspection manager 308may then transmit these commands to the monitoring device. However,other mechanisms for controlling the monitoring device are applicable aswell.

FIG. 12 is an operational flow diagram illustrating one example ofmanaging autonomous inspection of components within at least one area ofinterest. The operational flow diagram of FIG. 12 begins at step 1202and flows directly to step 1204. The inspection manager 308, at step1204 programs at least one mobile unmanned monitoring device toautonomously monitor at least one system component within an area ofinterest. For example, the inspection manager 308 may program the atleast one mobile unmanned monitoring device with one or more inspectionpaths to be traversed by the at least one mobile unmanned monitoringdevice with respect to the at least one system component; one or moreinspection parameters such as the type of data to capture; angles,resolution, etc. at which to capture images; time(s) at which totraverse the inspection path(s); and/or the like.

The inspection manager 308, at step 1206, receives inspection data fromthe receiving, from the at least one mobile unmanned monitoring device,inspection data generated by the at least one mobile unmanned monitoringdevice for the at least one system component. The at least one mobileunmanned monitoring device having generated the inspection data for theat least one system component. Examples of inspection data typesinclude, but are not limited to, image data, audio data, andenvironmental sensor data captured by the at least one mobile unmannedmonitoring and corresponding to the at least one system component.

The inspection manager 308, at step 1208, processes the inspection datautilizing one or more machine learning mechanisms. The inspectionmanager 310, at step 1210, determines a current operational state of theat least one system component based on processing the inspections data.In some embodiments, processing the inspection data further includesdetermining that additional inspection data is required, andelectronically instructing the at least one mobile unmanned monitoringdevice (or another monitoring device(s)) to traverse one or moreinspection paths and obtain additional inspection data with respect tothe at least one system component. The inspection manager 308, at step1210, autonomously generates a work order comprising a plurality ofcomponents addressing the current operational state of the at least onesystem component based on the operational state. In some embodiments,autonomously generating the work order comprises determining the currentoperational state of the at least one system component indicates the atleast one system component has experienced damage; determiningattributes of the damage; and determining, based on the attributes ofthe damage, one or more work crews required to repair the damage and atleast one of a set of parts required to repair the damage, and a set ofequipment required to repair the damage.

The inspection manager 308, at step 1212, autonomously provisions one ormore of the plurality of components for the work order. In someembodiments autonomously provisioning one or more of the plurality ofcomponents transmitting a communication to at least one otherinformation processing system indicating that the one or more pluralityof components have been assigned to the work order. The communicationmay further comprise instructions for the one or more plurality ofcomponents to be sent to a given location. The inspection manager 308,at step 1214, transforms one or more of the plurality of components intoan interactive component. When the interactive component is selected bya user at least a portion of the inspection data is presented to theuser. The control flow then exits at step 1216.

Referring now to FIG. 13 , this figure is a block diagram illustratingan information processing system that can be utilized in embodiments ofthe present invention. The information processing system 1302 is basedupon a suitably configured processing system configured to implement oneor more embodiments of the present invention such as the inspectionmanager 308 of FIG. 3 . The components of the information processingsystem 1302 can include, but are not limited to, one or more processorsor processing units 1304, a system memory 1306, and a bus 1308, whichcouples various system components including the system memory 1306 tothe processor 1304. The bus 1308 represents one or more of any ofseveral types of bus structures, including a memory bus or memorycontroller, a peripheral bus, an accelerated graphics port, and aprocessor or local bus using any of a variety of bus architectures. Byway of example, and not limitation, such architectures include IndustryStandard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus,Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA)local bus, and Peripheral Component Interconnects (PCI) bus.

The system memory 1306 may include computer system readable media in theform of volatile memory, such as random access memory (RAM) 1310 and/orcache memory 1312. The information processing system 1302 can furtherinclude other removable/non-removable, volatile/non-volatile computersystem storage media. By way of example only, a storage system 1314 canbe provided for reading from and writing to a non-removable orremovable, non-volatile media such as one or more solid state disksand/or magnetic media (typically called a “hard drive”). A magnetic diskdrive for reading from and writing to a removable, non-volatile magneticdisk (e.g., a “floppy disk”), and an optical disk drive for reading fromor writing to a removable, non-volatile optical disk such as a CD-ROM,DVD-ROM or other optical media can be provided. In such instances, eachcan be connected to the bus 1308 by one or more data media interfaces.The memory 1306 can include at least one program product having a set ofprogram modules that are configured to carry out the functions of anembodiment of the present invention.

Program/utility 1316, having a set of program modules 1318, may bestored in memory 1306 by way of example, and not limitation, as well asan operating system, one or more application programs, other programmodules, and program data. Each of the operating system, one or moreapplication programs, other program modules, and program data or somecombination thereof, may include an implementation of a networkingenvironment. Program modules 1318 generally carry out the functionsand/or methodologies of embodiments of the present invention.

The information processing system 1302 can also communicate with one ormore external devices 1320 such as a keyboard, a pointing device, adisplay 1322, etc.; one or more devices that enable a user to interactwith the information processing system 1302; and/or any devices (e.g.,network card, modem, etc.) that enable computer system/server 1302 tocommunicate with one or more other computing devices. Such communicationcan occur via I/O interfaces 1324. Still yet, the information processingsystem 1302 can communicate with one or more networks such as a localarea network (LAN), a general wide area network (WAN), and/or a publicnetwork (e.g., the Internet) via network adapter 1326. As depicted, thenetwork adapter 1326 communicates with the other components ofinformation processing system 1302 via the bus 1308. Other hardwareand/or software components can also be used in conjunction with theinformation processing system 1302. Examples include, but are notlimited to: microcode, device drivers, redundant processing units,external disk drive arrays, RAID systems, tape drives, and data archivalstorage systems.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method, or computer programproduct. Accordingly, one or more aspects of the present invention maytake the form of an entirely hardware embodiment, an entirely softwareembodiment (including firmware, resident software, micro-code, etc.) oran embodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit”, “module”, or “system”.Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention have been discussed above withreference to flowchart illustrations and/or block diagrams of methods,apparatus (systems) and computer program products according to variousembodiments of the invention. It will be understood that each block ofthe flowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer program instructions. These computer programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The description of the present invention has been presented for purposesof illustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

What is claimed is:
 1. A method, by an information processing system, ofmanaging an autonomous inspection of components within at least one areaof interest, the method comprising: responsive to determining that aweather event is expected to occur within an area of interest comprisingat least one system component, programming at least one mobile unmannedmonitoring device (MUMD) to perform a first autonomous inspection of theat least one system component prior to the weather event occurring;receiving, from the at least one MUMD, a first set of inspection datagenerated by the at least one MUMD for the at least one system componentbased on the first autonomous inspection; responsive to determining thatthe weather event has occurred within the area of interest, determiningthat the at least one MUMD is scheduled to perform a second autonomousinspection of the at least one system component at a first time that isafter a threshold amount of time has passed since the weather event hasoccurred; responsive to determining that the at least one MUMD isscheduled to perform the second autonomous inspection at the first time,programming the at least one MUMD to perform the second autonomousinspection of the at least one system component at a second time that isbefore the first time; receiving, from the at least one MUMD, a secondset of inspection data generated by the at least one MUMD for the atleast one system component based on the second autonomous inspection;determining a current operational state of the at least one systemcomponent based on the first set of inspection data and the second setof inspection data; and autonomously generating, based on the currentoperational state, a work order comprising a plurality of componentsaddressing the current operational state of the at least one systemcomponent.
 2. The method of claim 1, wherein programming at least oneMUMD to perform one or more of the first autonomous inspection or thesecond autonomous inspection comprises: programming the at least oneMUMD with one or more inspection paths to be traversed by the at leastone MUMD with respect to the at least one system component, and one ormore inspection parameters.
 3. The method of claim 1, wherein at leastone of first set of inspection data or the second set of inspection datacomprises at least one or more of image data, audio data, andenvironmental sensor data captured by the at least one MUMD andcorresponding to the at least one system component.
 4. The method ofclaim 1, wherein determining the current operational state of the atleast one system component comprises: determining that additionalinspection data is required; and electronically instructing the at leastone MUMD to traverse one or more inspection paths and obtain additionalinspection data with respect to the at least one system component. 5.The method of claim 1, wherein the plurality of components at leastcomprises: an identification of the current operational state of the atleast one system component; an identification of one or more work crewsassigned to the work order; and an identification of a set of partsrequired for addressing the current operational state.
 6. The method ofclaim 1, wherein determining the current operational state comprises atleast one of: determining that the at least one system component isdamaged; determining a type of the damage; determining a location of thedamage; or one or more combinations thereof.
 7. The method of claim 1,wherein autonomously generating the work order comprises: determiningthe current operational state of the at least one system componentindicates the at least one system component has experienced damage;determining attributes of the damage; and determining, based on theattributes of the damage, one or more work crews required to repair thedamage and at least one of a set of parts required to repair the damage,a set of equipment required to repair the damage, or a combinationthereof.
 8. The method of claim 1, further comprising: autonomouslyprovisioning one or more of the plurality of components for the workorder; presenting an interactive map of the area of interest includingan interactive icon associated with the at least one system component;determining that a user has selected the interactive icon; andresponsive to determining that the user has selected the interactiveicon, presenting the inspection data for the at least one systemcomponent and one or more components of the plurality of components forthe work order.
 9. The method of claim 1, further comprising:transmitting a communication to at least one information processingsystem indicating that the one or more of the plurality of componentshave been assigned to the work order, wherein the communication furthercomprises instructions for the one or more plurality of components to besent to a given location.
 10. An information processing system formanaging devices for managing an autonomous inspection of componentswithin at least one area of interest, the information processing systemcomprising: a processor; memory communicatively coupled to theprocessor; and an inspection manager communicatively coupled to theprocessor and the memory that, when operating, is configured to:responsive to a determination that a weather event is expected to occurwithin an area of interest comprising at least one system component,program at least one mobile unmanned monitoring device (MUMD) to performa first autonomous inspection of the at least one system component priorto the weather event occurring; receive, from the at least one MUMD, afirst set of inspection data generated by the at least one MUMD for theat least one system component based on the first autonomous inspection;responsive to a determination that the weather event has occurred withinthe area of interest, determine that the at least one MUMD is scheduledto perform a second autonomous inspection of the at least one systemcomponent at a first time that is after a threshold amount of time haspassed since the weather event has occurred; responsive to adetermination that the at least one MUMD is scheduled to perform thesecond autonomous inspection at the first time, program the at least oneMUMD to perform the second autonomous inspection of the at least onesystem component at a second time that is before the first time;receive, from the at least one MUMD, a second set of inspection datagenerated by the at least one MUMD for the at least one system componentbased on the second autonomous inspection; determine a currentoperational state of the at least one system component based on thefirst set of inspection data and the second set of inspection data; andautonomously generate, based on the current operational state, a workorder comprising a plurality of components addressing the currentoperational state of the at least one system component.
 11. Theinformation processing system of claim 10, wherein the inspectionmanager is configured to program the at least one MUMD to perform one ormore of the first autonomous inspection or the second autonomousinspection by: programming the at least one MUMD with one or moreinspection paths to be traversed by the at least one MUMD with respectto the at least one system component, and one or more inspectionparameters.
 12. The information processing system of claim 10, whereinthe inspection manager is further configured to: determine thatadditional inspection data is required; and electronically instruct theat least one MUMD to traverse one or more inspection paths and obtainadditional inspection data with respect to the at least one systemcomponent.
 13. The information processing system of claim 10, whereinthe inspection manager is configured to autonomously generate the workorder by: determining the current operational state of the at least onesystem component indicates the at least one system component hasexperienced damage; determining attributes of the damage; anddetermining, based on the attributes of the damage, one or more workcrews required to repair the damage and at least one of a set of partsrequired to repair the damage, a set of equipment required to repair thedamage, or a combination thereof.
 14. The information processing systemof claim 10, wherein the inspection manager is further configured toautonomously provision one or more components of the work order by:transmitting a communication to at least one information processingsystem that the one or more of the plurality of components have beenassigned to the work order, wherein the communication further comprisesinstructions for the one or more plurality of components to be sent to agiven location.
 15. A computer program product for managing anautonomous inspection of components within at least one area ofinterest, the computer program product comprising: a computer readablestorage medium having computer readable program code embodied therewith,the computer readable program code comprising instructions for:selecting at least one mobile unmanned monitoring device (MUMD) from aplurality of MUMDs based on one or more attributes of the at least oneMUMD and one or more attributes of at least one system component withinan area of interest; responsive to determining that a weather event isexpected to occur within the area of interest, programming the at leastone MUMD to perform a first autonomous inspection of the at least onesystem component prior to the weather event occurring; receiving, fromthe at least one MUMD, a first set of inspection data generated by theat least one MUMD for the at least one system component based on thefirst autonomous inspection; responsive to determining that the weatherevent has occurred within the area of interest, determining that the atleast one MUMD is scheduled to perform a second autonomous inspection ofthe at least one system component at a first time that is after athreshold amount of time has passed since the weather event hasoccurred; responsive to determining that the at least one MUMD isscheduled to perform the second autonomous inspection at the first time,programming the at least one MUMD to perform the second autonomousinspection of the at least one system component at a second time that isbefore the first time; receiving, from the at least one MUMD, a secondset of inspection data generated by the at least one MUMD for the atleast one system component based on the second autonomous inspection;processing, utilizing one or more machine learning mechanisms, the firstset of inspection data and the second set of inspection data;determining, based on the processing, a current operational state of theat least one system component; autonomously generating, based on thecurrent operational state, a work order comprising a plurality ofcomponents addressing the current operational state of the at least onesystem component; and autonomously provisioning one or more of theplurality of components for the work order.
 16. The computer programproduct of claim 15, wherein programming the at least one MUMD toperform at least one of the first autonomous inspection or the secondautonomous inspection comprises: programming the at least one MUMD withone or more inspection paths to be traversed by the at least one MUMDwith respect to the at least one system component, and one or moreinspection parameters.
 17. The computer program product of claim 15,wherein the computer readable program code further comprisesinstructions for: determining that additional inspection data isrequired; and electronically instruct the at least one MUMD to traverseone or more inspection paths and obtain additional inspection data withrespect to the at least one system component.
 18. The computer programproduct of claim 15, wherein autonomously generating the work ordercomprises: determining the current operational state of the at least onesystem component indicates the at least one system component hasexperienced damage; determining attributes of the damage; anddetermining, based on the attributes of the damage, one or more workcrews required to repair the damage and at least one of a set of partsrequired to repair the damage, a set of equipment required to repair thedamage, or a combination thereof.
 19. The computer program product ofclaim 15, wherein autonomously provisioning one or more components ofthe work order comprises: transmitting a communication to at least oneinformation processing system that the one or more of the plurality ofcomponents have been assigned to the work order, wherein thecommunication further comprises instructions for the one or moreplurality of components to be sent to a given location.
 20. The computerprogram product of claim 15, wherein autonomously generating the workorder comprises: determining the current operational state indicatesthat the at least one system component is damaged but is absent anidentification of a specific component of the at least one systemcomponent that is damaged; responsive to the current operational statebeing absent an identification of a specific component of the at leastone system component that is damaged, predicting, based on the weatherevent and the second set of inspection data, one or more components ofthe at least one system component that are damaged; and autonomouslygenerating the work order based on the predicted one or more componentsof the at least one system component that are damaged.